R (35 terms)

Rademacher Complexity Measures a model’s ability to fit random noise; used to bound generalization error. Intermediate RAG Architecture that retrieves relevant documents (e.g., from a vector DB) and conditions generation on them to reduce h... Intermediate Random Variable Variable whose values depend on chance. Advanced Rank Number of linearly independent rows or columns. Advanced ReAct Pattern Interleaving reasoning and tool use. Advanced Reality Gap Differences between simulated and real physics. Advanced Recall Of true positives, the fraction correctly identified; sensitive to false negatives. Intermediate Recurrent Neural Network Networks with recurrent connections for sequences; largely supplanted by Transformers for many tasks. Intermediate Red Teaming Stress-testing models for failures, vulnerabilities, policy violations, and harmful behaviors before release. Intermediate Reflection Prompting Asking model to review and improve output. Intro Reflex Agent Simple agent responding directly to inputs. Advanced Regularization Techniques that discourage overly complex solutions to improve generalization (reduce overfitting). Intermediate Reinforcement Learning A learning paradigm where an agent interacts with an environment and learns to choose actions to maximize cumulative ... Intermediate ReLU Activation max(0, x); improves gradient flow and training speed in deep nets. Intermediate Representation Learning Automatically learning useful internal features (latent variables) that capture salient structure for downstream tasks. Intermediate Reproducibility Ability to replicate results given same code/data; harder in distributed training and nondeterministic ops. Intermediate Residual Connection Allows gradients to bypass layers, enabling very deep networks. Intermediate Responsible AI A discipline ensuring AI systems are fair, safe, transparent, privacy-preserving, and accountable throughout lifecycle. Intermediate Restricted Boltzmann Machine Simplified Boltzmann Machine with bipartite structure. Intermediate Retrieval Prompt Prompt augmented with retrieved documents. Intro Reward Hacking Maximizing reward without fulfilling real goal. Advanced Reward Model Model trained to predict human preferences (or utility) for candidate outputs; used in RLHF-style pipelines. Intermediate Reward Shaping Modifying reward to accelerate learning. Advanced Rigid Body Dynamics Motion of solid objects under forces. Advanced Risk Model Quantifying financial risk. Intermediate Risk Register Central log of AI-related risks. Intermediate Risk Stratification Grouping patients by predicted outcomes. Intermediate RLHF Reinforcement learning from human feedback: uses preference data to train a reward model and optimize the policy. Intermediate Robotics Field combining mechanics, control, perception, and AI to build autonomous machines. Advanced Robust Alignment Maintaining alignment under new conditions. Advanced Robust Control Control that remains stable under model uncertainty. Intermediate ROC Curve Plots true positive rate vs false positive rate across thresholds; summarizes separability. Intermediate Role Prompting Assigning a role or identity to the model. Intro Rotary Positional Embeddings Encodes positional information via rotation in embedding space. Intermediate RRT Sampling-based motion planner. Advanced